https://github.com/benchopt/benchmark_quantile_regression
Benchopt benchmark for Quantile Regression
https://github.com/benchopt/benchmark_quantile_regression
Last synced: about 1 year ago
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Benchopt benchmark for Quantile Regression
- Host: GitHub
- URL: https://github.com/benchopt/benchmark_quantile_regression
- Owner: benchopt
- Created: 2021-03-29T20:52:24.000Z (about 5 years ago)
- Default Branch: main
- Last Pushed: 2023-07-05T08:30:24.000Z (almost 3 years ago)
- Last Synced: 2025-03-24T12:39:28.439Z (over 1 year ago)
- Language: Python
- Size: 17.6 KB
- Stars: 0
- Watchers: 3
- Forks: 4
- Open Issues: 5
-
Metadata Files:
- Readme: README.rst
Awesome Lists containing this project
README
Quantile Regression Benchmark
=============================
|Build Status| |Python 3.6+|
Benchopt is a package to simplify and make more transparent and
reproducible the comparisons of optimization algorithms.
This benchmark is dedicated to the the L1-regularized quantile regression problem:
$$\\min_{\\beta, \\beta_0} \\frac{1}{n} \\sum_{i=1}^{n} \\text{pinball}(y_i, x_i^\\top \\beta + \\beta_0) + \\lambda \\lVert \\beta \\rVert_1$$
where
$$\\text{pinball}(y, \\hat{y}) = \\alpha \\max(y - \\hat{y}, 0) + (1 - \\alpha) \\max(\\hat{y} - y, 0)$$
where $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features and
$$X = [x_1^\\top, \\dots, x_n^\\top]^\\top \\in \\mathbb{R}^{n \\times p}$$
Install
--------
This benchmark can be run using the following commands:
.. code-block::
$ pip install -U benchopt
$ git clone https://github.com/benchopt/benchmark_quantile_regression
$ benchopt run benchmark_quantile_regression
Apart from the problem, options can be passed to ``benchopt run``, to restrict the benchmarks to some solvers or datasets, e.g.:
.. code-block::
$ benchopt run benchmark_quantile_regression -s scipy -d simulated --max-runs 10 --n-repetitions 10
Use ``benchopt run -h`` for more details about these options, or visit https://benchopt.github.io/api.html.
.. |Build Status| image:: https://github.com/benchopt/benchmark_quantile_regression/workflows/Tests/badge.svg
:target: https://github.com/benchopt/benchmark_quantile_regression/actions
.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue
:target: https://www.python.org/downloads/release/python-360/